| Research Title |
Efficient Algorithms for Thai Tweet Summarization |
| Date of Distribution |
16 December 2016 |
| Conference |
| Title of the Conference |
icsec 2016, IEEE International Computer Science and Engineering Conference (ICSEC2016) |
| Organiser |
Maejo University |
| Conference Place |
Chiang Mai Orchid Hotel |
| Province/State |
Chiang Mai |
| Conference Date |
14 December 2016 |
| To |
17 December 2016 |
| Proceeding Paper |
| Volume |
2016 |
| Issue |
20 |
| Page |
56 |
| Editors/edition/publisher |
IEEE |
| Abstract |
Nowadays, Twitter is one of the most popular
microblogging services. A user may follow many people who
may post a 140 character status (tweet) often. Thus, if the user
does not continuously read tweets, users may find an excessive
number of unread tweets. Such incident causes a burden on the
user to find the relevant tweet. It is one of the reasons why
Twitter can lead users to feel overloaded with information. This
article implemented and evaluated six automatic summarization
algorithms for finding similar Thai tweets. The experimental
results showed that TextRank algorithm performed the best
because this algorithm selected the tweets with the highest scores.
On the other hand, Hybrid TF-IDF algorithm could detect
similar tweets the least because this algorithm calculated the
score by taking the sum frequency of words in a tweet instead
of considering the similarity in the level of sentences. |
| Author |
|
| Peer Review Status |
มีผู้ประเมินอิสระ |
| Level of Conference |
นานาชาติ |
| Type of Proceeding |
Abstract |
| Type of Presentation |
Oral |
| Part of thesis |
false |
| Presentation awarding |
false |
| Attach file |
|
| Citation |
0
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Publication
Journal Publication
ไทย